1. Field of the Invention
The present invention relates to a character location method. It also relates to character location in an image from a digital camera with a minimized use of computing power. More specifically the invention relates to a simple and robust connected component based scene character location algorithm for digital images.
2. Description of the Prior Art
Characters as descriptors are key objects in such fields as images or video databases, etc. It is ubiquitous in marks, indicators, billboards, video sequences, text documents, and so on. Thus character extraction and recognition are very important, and have many applications. For example, usability of information devices like a mobile phone is going to be more powerful with the help of optical character recognition (OCR) technology. Video sequences can be labeled or indexed automatically based on the recognized characters presented in a frame or a few frames. However, character location and extraction from images, especially scene images has proved to be difficult, due to the following reasons.
First, the characters are embedded in an image with other objects, such as structural bars, company logos and smears.
Second, the characters may be painted or printed in any color, and the background color may differ only slightly from that of the characters.
Third, the font, size and format of the characters may be different; and lastly, the lighting may be uneven.
Previous efforts to solve these problems are described in: S. Antani, et al. Robust extraction of text in video. Proceedings of IEEE 15th International Conference on Pattern Recognition. 831-834. In this article S. Antani, et al. take advantage of the temporal redundancy in video to detect and extract an unconstrained variety of text from general purpose video. This was done, by combining sub-pixel interpolation on individual frames, multiframe integration across time, character extraction filtering and recognition-based character segmentation.
Another effort to solve these problems is described in Yu Zhang, et al. Automatical caption localization in compressed video. IEEE Transactions on PAMI. 22(4): 385-392, 2000. On the basis of the intensity variation information encoded in the discrete cosine transform (DCT) domain, Yu Zhang, et al, presents a fast text captions method in JPEG compressed images and I-frames of MPEG compressed videos.
But most of the above mentioned efforts are focused on limited characters or controllable background. All the above approaches for pattern recognition algorithms have in common the requirement of substantial computing power. Therefore, they are not suitable for the use with mobile devices such as mobile terminal devices, mobile cameras, mobile phones, or handheld computers, due to low computing power, or low battery capacity.